Code Division Multiple Access (CDMA) systems are based on a digital wideband spread spectrum technology in which multiple independent user signals are transmitted across an allocated segment of the available radio spectrum. In CDMA, each user signal comprises a different orthogonal code and a pseudo random binary sequence that modulates a carrier, thereby spreading the spectrum of the waveform and thus allowing a large number of user signals to share the same frequency spectrum. The user signals are separated in the receiver with a correlator which allows only the signal with the selected orthogonal code to be de-spread. Other user signals whose codes do not match are not de-spread and as such contribute to system noise. The signal-to-noise ratio (SNR) of the system is determined by the ratio of the desired signal power to the sum of all interfering signals, enhanced by the system processing gain and the ratio of the spread bandwidth to the baseband data rate. In 3rd generation Wideband CDMA (WCDMA) different spreading factors and variable user data rates can be supported simultaneously.
By the use of spreading codes, the frequency band of a transmission signal is spread to a chip rate, which is larger than the actual data or information symbol rate. For example, if the used spreading code has the length of eight data symbols (referred to as “chips”), eight chips are transmitted for every data symbol. The property of unique codes is given by the property of orthogonality of the spreading codes meaning in mathematical terms that the inner product or correlation respectively of the spreading codes used or to use for communication is zero. Orthogonality of the spreading codes guarantees that transmission of a signal or sequence of data symbols respectively which is coded by a spreading code neither creates or propagates side effects to other signals coded by other orthogonal spreading codes and corresponding to other users of a communication system. A receiver looking for a certain spreading code of a certain transmitter will take signals coded by orthogonal spreading codes as a noise of the radio frequency (RF) channel. Since spreading codes can have different length, the property of orthogonality must be given also for spreading codes of different lengths.
Construction of a spreading code can be achieved by use of an orthogonal variable spreading factor (OVSF) tree as shown in FIG. 2, wherein the abbreviation “SF” designates the spreading factor characterizing the length of the spreading code and the level of the OVSF tree. Within each tree level, the available spreading codes have the same length and are orthogonal. The spreading factor may also be expressed by at the ratio between chip rate and data symbol rate or between chip duration and data symbol duration. Spreading codes of different users may fall into different levels in an OVSF tree thus providing various levels of quality of service (QoS). User symbols may be spread by spreading factors ranging from 4 to 512.
In CDMA systems in general, however, due to multipath propagation and frequency-selective fading, orthogonality between the various users waveforms is degraded and multiple access interference impairs the performance of the receiver. Although the transmitted user signals at the base station (BS) side are orthogonal, this orthogonality may no longer exist at a mobile station (MS) front-end due to multipath effects of the propagation channel between the transmitter and the receiver, which are caused by the fact that the channel may consist of more than one distinct propagation path for each signal of a user. Thus, multipath is a propagation phenomenon resulting in radio signals reaching the receiving antenna by two or more paths, so that the radio signals arrive at the receiver with different time delays. Causes of multipath propagation include atmospheric ducting, ionospheric reflection and refraction, and reflection from terrestrial objects, such as mountains and buildings.
FIG. 3 shows a typical CDMA communication system which comprises a plurality of mobile or user stations MS1, . . . , MSK and enables a plurality of users (1, . . . , K) to communicate with a base station BS1. Each of both the base station BS1 and mobile stations MS1, . . . , MSK comprise a transmitter TBS1, TMS1, . . . , TMSK and a receiver RBS1, RMS1, . . . , RMSK. The transmitter TBS1 of the base station BS transmits data in a downlink or forward link respectively to each of the user stations MS1, . . . , MSK and a receiver RBS1 of the base station BS1 receives data in an uplink or a reverse link respectively from each of the mobile user stations MS1, . . . , MSK. The air space between the base station BS1 and the mobile user stations MS1, . . . , MSK usually provides a multipath environment for both the uplink and the downlink communications represented as arrows in FIG. 3.
The following three common approaches have been used to circumvent the problem of loss of orthogonality or interference, respectively:
The first and most straight forward approach is to treat the generated interference due to multipath propagation as an additive white Gaussian noise (AWGN) and implement the conventional Rake receiver to detect symbols of a user independently from others by collecting the energy from a number of delayed forms of the received signal via correlations with the spreading code of that particular user.
The second approach is interference suppression, which partially brings back orthogonality via usage of chip rate channel equalisers and again estimates the symbols of a particular user independently from others via correlation with its spreading code.
Finally, the third approach is interference cancellation (IC). Firstly, the symbols of known active interfering spreading codes are estimated via methods in compassing one of the first two approaches. Then, the estimated symbols are re-spread, re-channeled and deleted from the originally received signals.
As already mentioned above, orthogonality may no longer exist at a MS front-end due to the multipath effect of the propagation channel between the transmitter and the receiver. This loss of orthogonality may cause inter-code interference (also known as multi-user interference or multi-access interference), inter-chip interference and inter-symbol interference in the symbol estimates. Receivers that are within the optimal or close-to-optimal category, i.e. multi-user detectors (MUDs) and interference cancellers (ICs), most of the time require knowledge about the signal and the channel parameters of all active users so as to mitigate the multipath effect and detect the desired data stream in most reliable ways. However, the possibility to implement MUDs or ICs in mobile stations is limited due to their high complexity and due to the fact that transmission parameters of all users are usually not known. A very practical and highly utilized sub-optimal solution is the conventional Rake receiver according to the above first approach, which performs a matched filter operation on the code of the desired user, such that multi-user interference is considered as an additional white noise.
However, when small spreading factors are used to achieve high data rates like, for example, in HSDPA systems, performance of the Rake receiver decreases due to the fact that the multipath interference becomes significant and the correlation characteristics of the spreading sequences are destroyed. For these reasons, equalisers according to the above second approach are considered for systems with small spreading factors in order to restore orthogonality between the users and limit interference, allowing to achieve higher data rates. This is particularly important for systems like HSDPA where the goal is to provide very high data rates.
In the UMTS standard, four QoS classes are defined with different delay and ordering needs. The four classes are conversational class with low delay and strict ordering (e.g. voice), streaming class with modest delay and strict ordering (e.g. video), interactive class with modest delay and modest ordering (e.g. web browsing), and background class with no delay guarantee and no ordering (e.g. bulk data transfer). Among these service classes, background class and interactive class have a bursty nature. This burstiness triggered the idea of users' time sharing of some of the resources, most importantly the orthogonal codes in the downlink, along with other supporting techniques, extensions, changes, removals applied on these channels. Hence, HSDPA has emerged as a system that would increase downlink data throughput by using fast physical layer retransmission and transmission combining and link adaptation controlled by the BS (or Node B in UMTS terminology). In HSDPA, two of the main features of WCDMA are disabled, namely variable spreading factor and fast power control. They are replaced by adaptive coding rate and adaptive modulation and extensive multi-code operations. The spreading factor is fixed to SF=16. A user can use up to 15 codes simultaneously, which enables a large dynamic range of HSDPA link adaptation and maintains good spectral efficiency. The scheduling process is done in the Node B so that it has the possibility of allocating or capacity to one user if necessary, and if the channel conditions make this strategy efficient.
To support the new HSDPA functionalities, two additional type of channels have been introduced. In the downlink direction from the BS or Node B to the MS, one or more shared control channels (HS-SCCHs) broadcast HSDPA channel assigned identities, transport format and hybrid automatic repeat request (HARQ) process identifier. In the uplink direction, a high speed dedicated physical control channel (HS-DPCCH) carries status reports for HARQ and channel quality indicators (CQIs).
The concept of equalisation based on the above second approach has been applied in different systems for several years. Consequently several equaliser schemes exist.
As an example, the U.S. Pat. No. 6,658,047 discloses an adaptive channel equaliser used in a receiver of a CDMA telecommunications system. An estimator for estimating an impulse response of a channel provides a reference for the adaptive equaliser, and the adaptive equaliser operates to estimate a transmitted chip sequence of the channel and restore orthogonality among the received signals. The adaptive equaliser includes circuitry for utilizing a blind adaptive algorithm, called Griffith algorithm, to estimate the transmitted chip sequence of the channel.
Additionally, Schniter P. et al., “Adaptive Chip-Rate Equalisation of Downlink Multirate Wideband CDMA”, IEEE Transactions on Signal Processing, Volume 53, Issue 6, June 2005, pp. 2205-2215, discloses a decision-directed (DD) chip-rate adaptive equalisation scheme aided by filtering and/or cancellation of multi-access interference (MAI). In the acquisition mode, a code-multiplexed pilot is used to adapt the equaliser from code start or loss-of-lock. The use of MAI filtering results in a 3rd-order least mean square (LMS) algorithm, which has significant advantages over a standard (i.e., 1st-order) LMS in non-stationary environments. In the tracking mode, decision-direction facilitates MAI-cancellation in the equaliser update, which enhances performance.
FIG. 4 shows a schematic block diagram of the DD chip-rate adaptive equalisation as described in the above prior art. In the DD mode, the receiver makes hard tentative decisions on all active users' symbols and uses them to construct a delayed, approximate copy of the transmitted sequence. The transmitted sequence is then used to update an adaptive filter at chip rate. Since it will not be possible to make reliable symbol estimates without a properly adjusted equaliser, the DD mode is only engaged after a preceding pilot-trained mode has converged. According to FIG. 4, the symbol estimation procedure comprises de-scrambling of the output of a tentative equaliser {circumflex over (f)}H(i) by multiplication with a de-scrambling signal s*(i−v). Then, a matched-filter output is computed for each active user in a de-spreading unit 4 and the matched-filter outputs are quantized in a detection unit 6. The hard symbol estimates and spreading codes are then used to regenerate a delayed, approximate copy of the multi-user sequence by re-spreading in a re-spreading unit 8 and multiplication by a re-scrambling signal s(i−Nmax−v). The re-scrambling operation yields a signal {circumflex over (t)}(i−Nmax−v). This re-scrambled signal is subtracted from the output of a second equaliser fH(i) to which a delayed input signal, which has been delayed by a delay of Nmax chips is supplied, wherein Nmax denotes the spreading gain of the lowest-rate user. Hence, two equaliser functions are provided, namely an Nmax-delayed equaliser function f(i−Nmax) which is adaptively updated and a tentative equaliser function {circumflex over (f)}(i) which is used to generate the symbol estimates. The tentative equalising function {circumflex over (f)}(i) can be computed in a prediction unit 2 using an Nmax-step forward prediction of the delayed equalising function f(i−Nmax). The adaptation of the delayed equaliser is performed based on a subtraction of the re-scrambled output {circumflex over (t)}(i−Nmax−v) from the output x(i−Nmax) of the delayed equaliser.
Under the HSDPA system, there are two possible phases during which the MS or user equipment (UE) in UMTS terminology can track (estimate) and/or equalize the channel, namely inactive and active phases. The inactive phase (or state) is when the user is listening to a channel but no high speed downlink shared channel (HSDSCH) has been assigned to him, while the active phase is given when at least one HSDSCH code has been assigned to him. The above adaptive equaliser described by Schniter et al. does not provide an optimal solution for high speed channels as provided in the HSDPA system. Due to the large delay introduced in the adaptation branch of the delayed equaliser, the adapted filter weights or taps cannot be directly used at the upper branch filtering operation of the tentative equaliser. In very fast changing channels, the prediction mechanism of the prediction unit 2 is essential to guess the upper branch filter weights of the tentative equaliser from the lower branch filter weights of the adaptive equaliser. Moreover, a substantial delay which corresponds to the maximum active spreading factor in the system is introduced and can even be 512 chips in some cases.
Additionally, in the adaptive equaliser scheme proposed by Schniter et al., knowledge of all active codes in the system is assumed. It is thus required to detect where the active codes reside in the OVSF hierarchy and estimate their amplitudes. This is however a very complicated process and hence not easy to implement. Even when implemented, problems of false detection, missing detection and wrongly estimated amplitudes may still occur. Moreover, de-spreading is done with each active code independently at various levels in the OVSF trees, which leads to a high computational complexity.